Workshops

Quality decision-making is based on your decision-making skills, and we all can improve our decision-making skills. That is the purpose of this workshop. As with any skill, improvement requires learning and understanding how to perform the elements of the skill well and then practicing the techniques to do them well.

This workshop presents concepts and procedures to address six fundamental elements necessary for making quality decisions:
- defining the decision that you want to face,
- identifying your values for that decision to describe what you hope to achieve, and then stating each of your values as an objective,
- creating alternatives better than those that were obvious and easy to identify,
- being proactive in creating your own decisions, referred to as decision opportunities, to raise your quality of life above where it currently is,
- removing constraints of others on alternatives that you desire to pursue by constructing alternatives so that an authorized decision-maker (e.g. one’s manager) will support the alternative you desire to pursue, and
- providing a consistent guide for all of your decisions by describing how to identify, organize, and use your strategic life objectives.

Concepts and procedures to develop the decision-making skills mentioned above are thoroughly described and illustrated by numerous real applications. Each of the concepts and procedures are practical to use and rely only on common sense and focused effort. The workshop will also have several short exercises to stress key ideas and demonstrate their importance for improving your decisions. Much of the material presented in the workshop is discussed in my new book titled Give Yourself a Nudge: Helping Smart People Make Smarter Personal and Business Decisions published by Cambridge Press in 2020.

About Ralph L. Keeney

Ralph L. Keeney is an expert on decision making and his passion is to help individuals and organizations improve their decision making skills. He received his doctorate from MIT, has been a professor at MIT, the University of Southern California, and Duke University, and created and managed the decision and risk analysis group in an engineering-environmental consulting firm. He is currently a consultant and lecturer on decision making.

Keeney is a member of the U.S. National Academy of Engineering and received an honorary doctorate from the University of Waterloo in Canada. He is the author of several books; the most recent is Give Yourself a Nudge: Helping Smart People Make Smarter Personal and Business Decisions (2020).

Many tools exist in the Decision Quality toolbox to gain insight from the practical incorporation of risks and uncertainties when evaluating alternatives and enabling informed decisions. This course provides a comprehensive overview appropriate for the novice, or expert alike, on the use of decision trees to clearly frame and communicate decision problems, scope options in real-time with rough numbers and evaluate alternatives to bring insight from probabilistic analysis. The goal is a clear understanding of the power of decision tree analysis and its role and utility in the all-important probabilistic toolbox.

An energy transition case study and model are used in the course to impart skill while learning how to approach these unique and important decisions being faced around the globe. The course balances large group discussions with hands-on small group breakouts. Beginning with decision tree theory, the problem is laid out and the decision frame prepared. An influence diagram introduces the model and allows for a discussion on how probabilistic tools link and work with Excel. Tornado sensitivity analysis is introduced, and hands-on exercises generate tornados and compare alternatives to mine for insight. After deciding the impactful uncertainties to include in the probabilistic analysis, decision trees are built, and cumulative probability curves generated. The results are filtered during small group exercises to understand the impact of different “what-if” events and brainstorm hybrid strategies to manage risk in the path to meeting energy transition goals and creating value.

About Ellen Coopersmith

Ellen Coopersmith is an expert in decision quality and decision analysis implementation and its practical application in multiple industries. She consults, facilitates, and trains organizations across the globe, utilizing her extensive experience in strategy development, scenario planning, decision framing, probabilistic analysis, and value of information. An engineer by degree from The Colorado School of Mines, Ms. Coopersmith has specialized in decision analysis for last 25+ years. As of 2022, she’s trained over 7,500 professionals while assisting companies with both corporate DQ implementations and strategic decisions at all levels of the organization. Ms. Coopersmith is the president of Decision Frameworks, a decision quality enablement firm providing consulting, training and software around the globe. She was the 2017 – 2018 president of the Society of Decision Professionals, a published speaker on decision analysis, a Professional Engineer and SDP Fellow.

About Jan Schulze

Jan is a Vice President at Decision Frameworks and has led the company’s software development within since 2005. He’s an excellent decision analyst practitioner and instructor, although he specializes in software engineering, software development, user interaction and user interface design, and high performance computing.

He has a BSc Hons in Computer Science and Business from Warwick University and was Previously a Software Developer at Merak and Schlumberger, as well as a member of SDP and SPE.

In this workshop you will learn how to place a value on data or information before obtaining it. For example, how much should you be willing to pay for a well test, a clinical trial, a COVID-19 test?

Value of information (VOI) is a fundamental concept within decision analysis and one of its most interesting applications. All decision professionals should have a firm grasp of the VOI concept, know how to calculate it, and understand its properties. This includes understanding many fallacies, such as the belief that the value of information is the greatest when we are the most uncertain.

We will begin by understanding how we can and should learn from data. That is, how can we move (inversely) from an observation (e.g., a medical test result) to estimate the probability of the underlying cause (e.g., the presence of a pathogen)? This is an old question, which we will place in a historical context, beginning with the work of Thomas Bayes and Pierre-Simon Laplace.

Once we understand how to reason from observations, the next step is to use that information to make better decisions. To accomplish this, we will introduce the necessary decision analysis concepts of decision trees and risk aversion. With these tools, we will be able to place a value being able to act with perfect foresight (i.e., the value of perfect information), which places an upper limit on all information gathering activities. We will then discuss how to modify our analysis when the information it not perfect. With this knowledge, we will dispel many widely held, but incorrect, beliefs regarding the properties of VOI.

Finally, we will discuss decisions in which we can learn over time and how to model dynamic VOI problems. Examples include exploration in the oil & gas industry and indication sequencing of pharmaceuticals.

We will illustrate the tools and concepts discussed during the workshop using examples taken from a variety of industries, including oil and gas and life sciences.

About Eric Bickel

J. Eric Bickel is a professor in both the Operations Research & Industrial Engineering (ORIE) graduate program and the Department of Information, Risk, and Operations Management (IROM) at The University of Texas at Austin. His research interests include the theory and practice of decision analysis. He is past president of the Decision Analysis Society and a Fellow of the Society of Decision Professionals. Prof. Bickel joined Strategic Decisions Group in 1995, where he remains a partner and member of the board of directors. He has practiced decision analysis for over 25 years in a range of industries including oil & gas, electric power, life sciences, financial services, metals and mining, and packaging. He holds an MS and PhD from the Department of Engineering-Economic Systems at Stanford University.

Business decisions face many challenges in today’s VUCA (Volatile, Uncertain, Complex, and Ambiguous) world, making it hard to see through the fog in highly complex, contradictory situations. Yet, in the artificial, extreme worlds of scenario planning, strategic implications of possible future realities become very apparent providing a unique opportunity to develop robust strategy. Scenario Planning for Strategy Development helps navigate the uncertain future by providing a comprehensive framework to identify, classify and develop strategies to mitigate key external uncertainties.

Attend this course and learn to broaden your decision frames to address business landscape uncertainties, develop winning strategies for different possible future worlds, and qualitatively assess their robustness across a breadth of future scenarios. You will work an interesting green technology business expansion case which explores taking a successful product line to new, promising markets with uncertain business landscapes. Sound familiar? Learn a practical and repeatable workflow that enables you to facilitate scenario thinking easily to increase the chance of success for your own business expansion decisions.

About Ellen Coopersmith

Ellen Coopersmith is an expert in decision quality and decision analysis implementation and its practical application in multiple industries. She consults, facilitates, and trains organizations across the globe, utilizing her extensive experience in strategy development, scenario planning, decision framing, probabilistic analysis, and value of information. An engineer by degree from The Colorado School of Mines, Ms. Coopersmith has specialized in decision analysis for last 25+ years. As of 2022, she’s trained over 7,500 professionals while assisting companies with both corporate DQ implementations and strategic decisions at all levels of the organization. Ms. Coopersmith is the president of Decision Frameworks, a decision quality enablement firm providing consulting, training and software around the globe. She was the 2017 – 2018 president of the Society of Decision Professionals, a published speaker on decision analysis, a Professional Engineer and SDP Fellow.

About Jan Schulze

Jan is a Vice President at Decision Frameworks and has led the company’s software development within since 2005. He’s an excellent decision analyst practitioner and instructor, although he specializes in software engineering, software development, user interaction and user interface design, and high performance computing.

He has a BSc Hons in Computer Science and Business from Warwick University and was Previously a Software Developer at Merak and Schlumberger, as well as a member of SDP and SPE.